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Kiting in RTS Games Using Influence Maps Alberto Uriarte and Santiago Ontañón Drexel University Philadelphia 1/26 October 9, 2012
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2/26 Outline Introduction Problem Statement StarCraft and NOVA An Influence Map Approach to Kiting When Can Kiting Be Performed? Influence Maps for Kiting Target Selection Kiting Algorithm Empirical Evaluation 3 Different experiments Conclusions and Future Work
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http://www.xkcd.com/1002/ Introduction 3/26
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4/26 Introduction picture from Ben Weber What is a Real-Time Strategy Game? Macro Management Micro Management
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5/26 Introduction Adversarial planning under uncertainty Learning and opponent modeling Spatial and temporal reasoning Challenges All of this under real-time constrains
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6/26 Problem Statement What is kiting?
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7/26 Problem Statement What is kiting? AB Attack Range
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8/26 Problem Statement What is kiting? A B Kiting: A exhibits a kiting behavior when it keeps a safe distance from B to reduce the damage taken from attacks of B while B keeps pursuing A. Kiting: A exhibits a kiting behavior when it keeps a safe distance from B to reduce the damage taken from attacks of B while B keeps pursuing A.
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9/26 Problem Statement What is kiting? B A Perfect Kiting: When A is able to inflict damage to B without suffering any damage in return. Perfect Kiting: When A is able to inflict damage to B without suffering any damage in return.
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10/26 Problem Statement What is kiting? B Sustained Kiting: When A is not able to cause enough damage to kill unit B, but B is also unable to kill A. Sustained Kiting: When A is not able to cause enough damage to kill unit B, but B is also unable to kill A. A
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11/26 Problem Statement What is kiting?
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12/26 StarCraft and NOVA Information Manager Strategy Manager Build Manager Planner Manager Squad Manager Squad Agent Production Manager Worker Manager Squad Agent Combat Agent
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13/26 An Influence Map Approach to Kiting When Can Kiting Be Performed? 1. AB
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turn 1 14/26 An Influence Map Approach to Kiting When Can Kiting Be Performed? 1. 2. A B deceleration A attack time turn 2 A acceleration
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15/26 An Influence Map Approach to Kiting When Can Kiting Be Performed? 1. 2. A B
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16/26 An Influence Map Approach to Kiting Influence Map Abstract information of relevant areas (numerical influence). Spatial partition (walk tile map).
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17/26 An Influence Map Approach to Kiting Influence Map 333 33333 3333 33333 333 Influence Fields Enemy unit
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18/26 An Influence Map Approach to Kiting Influence Map 1111111 1114441 33344 3344 33344 3341 11 Influence Fields Walls
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19/ An Influence Map Approach to Kiting Influence Map Example
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20/30 An Influence Map Approach to Kiting Target Selection
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21/30 An Influence Map Approach to Kiting Kiting Algorithm tick() { target = targetSelection(); if (canKite(target)) { kitingAttack(target); } else { attack(target); } kitingAttack(target) { position = getSecurePosition(actualPos); if (position == actualPos) { attack(target); } else { move(position); // flee movement }
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22/30 Empirical Evaluation Experiment 1 – 1 Vulture vs 6 Zealots vs Settings: 1.Default behavior 2.Influence Map (enemy) 3.Influence Map (enemy + walls) 4.IM + Target Selection (perfect kiting) After 1.000 games with each setting Setting1234 Games won 0.0 %24.9 %85.5 %95.2 %
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23/30 Empirical Evaluation Experiment 2 – 4 Vultures vs 6 Zealots vs Settings: 1.Default behavior 2.Influence Map (enemy) 3.Influence Map (enemy + walls) 4.IM + Target Selection (perfect kiting) After 1.000 games with each setting Setting1234 Games won 0.0 %98.8 %100 %
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24/30 Empirical Evaluation Comparison between experiment 1 and 2 Experiment 1Experiment 2
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25/30 Empirical Evaluation Experiment 3 – 1 Full Game vs Settings: 1.Default behavior 2.Influence Map (enemy) 3.Influence Map (enemy + walls) 4.IM + Target Selection (perfect kiting) After 1.000 games with each setting Setting14 Games won 17.6 % 96.0 % AIIDE 2011 Competition: http://www.youtube.com/watch?feature=player_detailpage&v=xXsx1ma3_ko#t=225s
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26/30 Conclusions and Future Work Conclusions Future work Huge improvement when kiting is possible % victories increases 445.45% !!! Computationally tractable to be used in real-time conditions More complex kiting behavior Earn time Ambush (cooperation)
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